Host-pathogen interactions of COVID-19 involve biophysical mechanisms and complex dynamics from the subcellular to organismal scales. The outcome and timing of events in individual patients, from recovery to potentially lethal scenarios like sepsis and cytokine storm, emerge from such complex interactions and vary widely by patient and virus. Simulations of tissue-specific effects of primary acute viral infections like COVID-19 are essential for understanding differences in disease outcomes and optimizing therapeutic interventions. This workshop presents an open-source Python- and XML-scripted multiscale modeling and simulation framework of an epithelial tissue infected by a virus, a simplified cellular immune response and viral and immune-induced tissue damage and shows how to use it to model basic patterns of infection dynamics. Adding to and extending the framework by the scientific community through built-in modularity and extensibility is demonstrated with examples of modeling of tissue repair. Attendees will interactively launch and run the framework in the workshop using a web-based deployment, and investigate the effects of manipulating basic mechanisms of viral infection and immune response on emergent outcomes.

Engineered nanoBIO Node at Indiana University

Researchers should cite this work as follows:

• T.J. Sego (2020), "Understanding COVID-19 Infection, Immune Response, and Drug Therapy through Multiscale, Multicellular Modeling and Simulation," https://nanohub.org/resources/34578.

  BibTex | EndNote

1. CompuCell3D
2. COVID19
3. drug therapy
4. immune response
5. interactions
6. multiscale modeling and simulation
7. NanoBio Node at Indiana
8. RNA synthesis
9. SARS-Cov-2
10. simulation and modeling
11. Virus
12. viruses